Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7358273 | Journal of Econometrics | 2017 | 16 Pages |
Abstract
This paper constructs an estimator for the number of common factors in a setting where both the sampling frequency and the number of variables increase. Empirically, we document that the covariance matrix of a large portfolio of US equities is well represented by a low rank common structure with sparse residual matrix. When employed for out-of-sample portfolio allocation, the proposed estimator largely outperforms the sample covariance estimator.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Yacine Aït-Sahalia, Dacheng Xiu,